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Macroeconomic Forecasting and Structural Change

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  • Antonello D'Agostino
  • Luca Gambetti
  • Domenico Giannone

Abstract

The aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts. We produce real time out-of-sample forecasts for inflation, the unemployment rate and the interest rate using a Time-Varying Coe±cients VAR with Stochastic Volatility (TV-VAR) for the US. The model generates accurate predictions for the three variables. In particular for inflation the TV-VAR outperforms, in terms of mean square forecast error, all the competing models: fixed coefficients VARs, Time-Varying ARs and the naaive random walk model. These results are also shown to hold over the most recent period in which it has been hard to forecast inflation.

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Bibliographic Info

Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number 2009_020.

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Length: 29 p.
Date of creation: 2009
Date of revision:
Publication status: Published by:
Handle: RePEc:eca:wpaper:2009_020

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Keywords: Forecasting; infation; stochastic Volatility; time varying vector autoregression.;

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References

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  1. Clarida, Richard & Galí, Jordi & Gertler, Mark, 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," CEPR Discussion Papers 1908, C.E.P.R. Discussion Papers.
  2. John M. Roberts, 2006. "Monetary Policy and Inflation Dynamics," International Journal of Central Banking, International Journal of Central Banking, vol. 2(3), September.
  3. Tatevik Sekhposyan & Barbara Rossi, 2008. "Has modelsí forecasting performance for US output growth and inflation changed over time, and when?," Working Papers 09-02, Duke University, Department of Economics.
  4. Domenico Giannone & Michele Lenza & Lucrezia Reichlin, 2008. "Explaining The Great Moderation: It Is Not The Shocks," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 621-633, 04-05.
  5. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
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  7. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
  8. Canova, Fabio, 2007. "G-7 Inflation Forecasts: Random Walk, Phillips Curve Or What Else?," Macroeconomic Dynamics, Cambridge University Press, vol. 11(01), pages 1-30, February.
  9. D''Agostino, Antonello & Giannone, Domenico & Surico, Paolo, 2007. "(Un)Predictability and Macroeconomic Stability," CEPR Discussion Papers 6594, C.E.P.R. Discussion Papers.
  10. Timothy Cogley & Argia M. Sbordone, 2006. "Trend inflation and inflation persistence in the New Keynesian Phillips curve," Staff Reports 270, Federal Reserve Bank of New York.
  11. Timothy Cogley & Sergei Morozov & Thomas J. Sargent, 2003. "Bayesian Fan Charts for U.K. Inflation: Forecasting and Sources of Uncertainty in an Evolving Monetary System," CFS Working Paper Series 2003/44, Center for Financial Studies.
  12. James H. Stock & Mark W. Watson, 1994. "Evidence on Structural Instability in Macroeconomic Time Series Relations," NBER Technical Working Papers 0164, National Bureau of Economic Research, Inc.
  13. Douglas Staiger & James H. Stock & Mark W. Watson, 2001. "Prices, Wages and the U.S. NAIRU in the 1990s," NBER Working Papers 8320, National Bureau of Economic Research, Inc.
  14. Todd E. Clark & Michael W. McCracken, 2007. "Forecasting with small macroeconomic VARs in the presence of instabilities," Finance and Economics Discussion Series 2007-41, Board of Governors of the Federal Reserve System (U.S.).
  15. Pivetta, Frederic & Reis, Ricardo, 2007. "The persistence of inflation in the United States," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1326-1358, April.
  16. Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
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